Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Saed Rezayi"'
Publikováno v:
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) ISBN: 9781611977653
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9dd17748f03eab00b32fe83897237af0
https://doi.org/10.1137/1.9781611977653.ch104
https://doi.org/10.1137/1.9781611977653.ch104
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::300e60385389d9a03390d61648f7ffe0
https://doi.org/10.1109/wacv56688.2023.00401
https://doi.org/10.1109/wacv56688.2023.00401
Autor:
Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Chen Zhen, Tianming Liu, Sheng Li
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Pretraining domain-specific language models remains an important challenge which limits their applicability in various areas such as agriculture. This paper investigates the effectiveness of leveraging food related text corpora (e.g., food and agricu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fd7c047fa2acc3e8e66e92676ca98b2
https://doi.org/10.24963/ijcai.2022/715
https://doi.org/10.24963/ijcai.2022/715
Autor:
Saed Rezayi, Haixing Dai, Zhengliang Liu, Zihao Wu, Akarsh Hebbar, Andrew H. Burns, Lin Zhao, Dajiang Zhu, Quanzheng Li, Wei Liu, Sheng Li, Tianming Liu, Xiang Li
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783031210136
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94677bd816a859b46567355c32a719e0
https://doi.org/10.1007/978-3-031-21014-3_28
https://doi.org/10.1007/978-3-031-21014-3_28
Autor:
Saed Rezayi, Nedim Lipka, Vishwa Vinay, Ryan A. Rossi, Franck Dernoncourt, Tracy H. King, Sheng Li
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::611b7a9e9121f3aa2ea9177ad46eeaf3
https://doi.org/10.1109/bigdata52589.2021.9671344
https://doi.org/10.1109/bigdata52589.2021.9671344
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:13035-13036
In this work we propose a scheme, called XDC, that uses adversarial learning to train an adaptive cross domain clustering model. XDC trains a classifier on a labeled dataset and assigns labels to an unlabeled dataset. We benefit from adversarial lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffe5349e24a0a8ed32665a7aafb0340a
https://doi.org/10.1609/aaai.v36i11.21654
https://doi.org/10.1609/aaai.v36i11.21654
Publikováno v:
MIPR
The importance of fake news detection and classification on Online Social Networks (OSN) has recently increased and drawn attention. Training machine learning models for this task requires different types of attributes or modalities for the target OS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66e1dc0b0bcf23671248e35ff7fa737a
https://doi.org/10.1109/mipr51284.2021.00048
https://doi.org/10.1109/mipr51284.2021.00048
Publikováno v:
NAACL-HLT
Knowledge graphs suffer from sparsity which degrades the quality of representations generated by various methods. While there is an abundance of textual information throughout the web and many existing knowledge bases, aligning information across the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a7cdf27bd93813ee69e18e0844f23a9
https://doi.org/10.18653/v1/2021.naacl-main.221
https://doi.org/10.18653/v1/2021.naacl-main.221
Publikováno v:
2018 International Conference on Computational Science and Computational Intelligence (CSCI).
The right to freedom of expression is a very crucial element to form democratic, non polarized societies, and as much as it is fundamental to establish a genuine democracy, it can throw it off the track. The widespread growth of different types of on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30f49eacbcf2e101c5a39b5ad7e7bb69
https://doi.org/10.1109/csci46756.2018.00010
https://doi.org/10.1109/csci46756.2018.00010
Publikováno v:
ASONAM
The most-followed Twitter users and their pairwise relationships form a sub-graph of all Twitter users that we call the Twitter elite network. The connectivity patterns and influence (in terms of reply and retweet activity) among these elite users il
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cdc70abae7c419cdfaacdcbb8851b01
https://doi.org/10.1109/asonam.2018.8508252
https://doi.org/10.1109/asonam.2018.8508252